Offline handwriting segmentation for writer identification

In this paper we present a new technique for off-line text-independent handwriting analysis based on segmentation. Segmentation is a common step used in different research works in order to generate connected components that will be processed to extract features (geometry, concavity etc.). Our work focuses in the segmentation process and the information that can be directly extracted from the way a writer joins or separates ink connected components without need of analyzing the components themselves. The proposed multi-segmentation method shows good results tested on its own with real documents from police corps database and suggest an improved way to apply segmentation to other connected component based systems.